Interface to the 'Pharmpy' 'Pharmacometrics' Library
add_iov
add_lag_time
add_metabolite
add_parameter_uncertainty_step
add_pd_iiv
calculate_eta_shrinkage
calculate_se_from_cov
calculate_se_from_prec
calculate_ucp_scale
check_dataset
check_high_correlations
check_parameters_near_bounds
Checks version of Pharmpy/pharmr
cleanup_model
convert_model
create_basic_pk_model
create_config_template
evaluate_weighted_residuals
expand_additional_doses
filter_dataset
find_clearance_parameters
find_volume_parameters
fit
fix_or_unfix_parameters
fix_parameters
fix_parameters_to
get_admid
get_baselines
get_bioavailability
get_central_volume_and_clearance
get_cmt
get_concentration_parameters_from_data
get_config_path
get_covariate_baselines
get_covariate_effects
get_doseid
get_doses
get_dv_symbol
get_evid
get_ids
has_additive_error_model
has_combined_error_model
has_covariate_effect
has_first_order_absorption
has_first_order_elimination
has_instantaneous_absorption
has_linear_odes
has_linear_odes_with_real_eigenvalues
has_michaelis_menten_elimination
has_mixed_mm_fo_elimination
has_odes
has_presystemic_metabolite
has_proportional_error_model
has_random_effect
has_seq_zo_fo_absorption
has_weighted_error_model
has_zero_order_absorption
has_zero_order_elimination
Install Pharmpy
Install Pharmpy (with specified version)
is_linearized
is_real
is_strictness_fulfilled
list_time_varying_covariates
load_dataset
load_example_model
load_example_modelfit_results
make_declarative
mu_reference_model
omit_data
plot_abs_cwres_vs_ipred
plot_cwres_vs_idv
plot_dv_vs_ipred
plot_dv_vs_pred
plot_eta_distributions
plot_individual_predictions
plot_iofv_vs_iofv
plot_transformed_eta_distributions
run_iivsearch
set_estimation_step
set_evaluation_step
set_first_order_absorption
set_first_order_elimination
set_iiv_on_ruv
set_initial_condition
summarize_modelfit_results
unfix_parameters
unfix_parameters_to
unload_dataset
update_initial_individual_estimates
use_thetas_for_error_stdev
write_csv
write_model
write_results
get_observations
get_omegas
add_admid
calculate_eta_gradient_expression
get_number_of_peripheral_compartments
get_number_of_transit_compartments
get_observation_expression
get_parameter_rv
get_pd_parameters
get_pk_parameters
get_population_prediction_expression
get_rv_parameters
get_sigmas
get_thetas
get_unit_of
get_zero_order_inputs
greekify_model
read_model
read_model_from_string
read_modelfit_results
read_results
remove_bioavailability
remove_covariate_effect
retrieve_models
add_allometry
add_bioavailability
add_cmt
add_covariate_effect
add_derivative
add_effect_compartment
add_estimation_step
add_iiv
add_indirect_effect
add_individual_parameter
calculate_cov_from_prec
add_peripheral_compartment
add_pk_iiv
add_population_parameter
add_predictions
add_residuals
add_time_after_dose
append_estimation_step_options
calculate_epsilon_gradient_expression
bin_observations
bump_model_number
calculate_aic
calculate_bic
calculate_corr_from_cov
calculate_corr_from_prec
calculate_cov_from_corrse
calculate_individual_parameter_statistics
calculate_individual_shrinkage
calculate_parameters_from_ucp
calculate_pk_parameters_statistics
calculate_prec_from_corrse
calculate_prec_from_cov
create_joint_distribution
create_report
create_rng
create_symbol
deidentify_data
display_odes
drop_columns
drop_dropped_columns
evaluate_epsilon_gradient
evaluate_eta_gradient
evaluate_expression
evaluate_individual_prediction
evaluate_population_prediction
get_individual_parameters
get_individual_prediction_expression
get_initial_conditions
get_lag_times
get_mdv
get_model_code
get_model_covariates
get_number_of_individuals
get_number_of_observations
get_number_of_observations_per_individual
plot_vpc
predict_influential_individuals
predict_influential_outliers
predict_outliers
print_fit_summary
print_model_code
print_model_symbols
Print pharmpy version
read_dataset_from_datainfo
remove_derivative
remove_error_model
remove_estimation_step
remove_iiv
remove_iov
remove_lag_time
remove_loq_data
remove_parameter_uncertainty_step
set_peripheral_compartments
remove_peripheral_compartment
remove_predictions
remove_residuals
remove_unused_parameters_and_rvs
rename_symbols
replace_non_random_rvs
resample_data
Reset index
Reset result indices
run_allometry
run_amd
run_bootstrap
run_covsearch
run_estmethod
run_iovsearch
run_linearize
run_modelfit
run_modelsearch
run_retries
run_ruvsearch
run_simulation
run_structsearch
run_tool
sample_individual_estimates
sample_parameters_from_covariance_matrix
sample_parameters_uniformly
set_additive_error_model
set_baseline_effect
set_combined_error_model
set_covariates
set_dataset
set_direct_effect
set_dtbs_error_model
set_dvid
set_initial_estimates
set_instantaneous_absorption
set_lloq_data
set_lower_bounds
set_michaelis_menten_elimination
set_mixed_mm_fo_elimination
set_name
set_ode_solver
set_power_on_ruv
set_proportional_error_model
set_reference_values
set_seq_zo_fo_absorption
set_simulation
set_time_varying_error_model
split_joint_distribution
set_tmdd
set_transit_compartments
set_upper_bounds
set_weighted_error_model
set_zero_order_absorption
set_zero_order_elimination
set_zero_order_input
simplify_expression
solve_ode_system
transform_blq
transform_etas_boxcox
transform_etas_john_draper
transform_etas_tdist
translate_nmtran_time
unconstrain_parameters
undrop_columns
Interface to the 'Pharmpy' 'pharmacometrics' library. The 'Reticulate' package is used to interface Python from R.